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// SPDX-License-Identifier: GPL-3.0-or-later
#include "nml.h"
#include <random>
bool ml_capable() {
return true;
}
bool ml_enabled(RRDHOST *rh) {
if (!Cfg.enable_anomaly_detection)
return false;
if (simple_pattern_matches(Cfg.sp_host_to_skip, rrdhost_hostname(rh)))
return false;
return true;
}
/*
* Assumptions:
* 1) hosts outlive their sets, and sets outlive their dimensions,
* 2) dimensions always have a set that has a host.
*/
void ml_init(void) {
// Read config values
nml_config_load(&Cfg);
if (!Cfg.enable_anomaly_detection)
return;
// Generate random numbers to efficiently sample the features we need
// for KMeans clustering.
std::random_device RD;
std::mt19937 Gen(RD());
Cfg.random_nums.reserve(Cfg.max_train_samples);
for (size_t Idx = 0; Idx != Cfg.max_train_samples; Idx++)
Cfg.random_nums.push_back(Gen());
// start detection & training threads
char tag[NETDATA_THREAD_TAG_MAX + 1];
snprintfz(tag, NETDATA_THREAD_TAG_MAX, "%s", "PREDICT");
netdata_thread_create(&Cfg.detection_thread, tag, NETDATA_THREAD_OPTION_JOINABLE, nml_detect_main, NULL);
}
void ml_host_new(RRDHOST *rh) {
if (!ml_enabled(rh))
return;
nml_host_t *host = nml_host_new(rh);
rh->ml_host = reinterpret_cast<ml_host_t *>(host);
}
void ml_host_delete(RRDHOST *rh) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rh->ml_host);
if (!host)
return;
nml_host_delete(host);
rh->ml_host = NULL;
}
void ml_chart_new(RRDSET *rs) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rs->rrdhost->ml_host);
if (!host)
return;
nml_chart_t *chart = nml_chart_new(rs);
rs->ml_chart = reinterpret_cast<ml_chart_t *>(chart);
}
void ml_chart_delete(RRDSET *rs) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rs->rrdhost->ml_host);
if (!host)
return;
nml_chart_t *chart = reinterpret_cast<nml_chart_t *>(rs->ml_chart);
nml_chart_delete(chart);
rs->ml_chart = NULL;
}
void ml_dimension_new(RRDDIM *rd) {
nml_chart_t *chart = reinterpret_cast<nml_chart_t *>(rd->rrdset->ml_chart);
if (!chart)
return;
nml_dimension_t *dim = nml_dimension_new(rd);
rd->ml_dimension = reinterpret_cast<ml_dimension_t *>(dim);
}
void ml_dimension_delete(RRDDIM *rd) {
nml_dimension_t *dim = reinterpret_cast<nml_dimension_t *>(rd->ml_dimension);
if (!dim)
return;
nml_dimension_delete(dim);
rd->ml_dimension = NULL;
}
void ml_get_host_info(RRDHOST *rh, BUFFER *wb) {
if (rh && rh->ml_host) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rh->ml_host);
nml_host_get_config_as_json(host, wb);
} else {
buffer_json_member_add_boolean(wb, "enabled", false);
}
}
char *ml_get_host_runtime_info(RRDHOST *rh) {
nlohmann::json config_json;
if (rh && rh->ml_host) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rh->ml_host);
nml_host_get_detection_info_as_json(host, config_json);
} else {
return NULL;
}
return strdup(config_json.dump(1, '\t').c_str());
}
char *ml_get_host_models(RRDHOST *rh) {
nlohmann::json j;
if (rh && rh->ml_host) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rh->ml_host);
nml_host_get_models_as_json(host, j);
return strdup(j.dump(2, '\t').c_str());
}
return NULL;
}
bool ml_chart_update_begin(RRDSET *rs) {
nml_chart_t *chart = reinterpret_cast<nml_chart_t *>(rs->ml_chart);
if (!chart)
return false;
nml_chart_update_begin(chart);
return true;
}
void ml_chart_update_end(RRDSET *rs) {
nml_chart_t *chart = reinterpret_cast<nml_chart_t *>(rs->ml_chart);
if (!chart)
return;
nml_chart_update_end(chart);
}
bool ml_is_anomalous(RRDDIM *rd, time_t curr_time, double value, bool exists) {
nml_dimension_t *dim = reinterpret_cast<nml_dimension_t *>(rd->ml_dimension);
if (!dim)
return false;
nml_chart_t *chart = reinterpret_cast<nml_chart_t *>(rd->rrdset->ml_chart);
bool is_anomalous = nml_dimension_predict(dim, curr_time, value, exists);
nml_chart_update_dimension(chart, dim, is_anomalous);
return is_anomalous;
}
bool ml_streaming_enabled() {
return Cfg.stream_anomaly_detection_charts;
}
void ml_start_training_thread(RRDHOST *rh) {
if (rh && rh->ml_host) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rh->ml_host);
nml_host_start_training_thread(host);
}
}
void ml_stop_training_thread(RRDHOST *rh) {
if (rh && rh->ml_host) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rh->ml_host);
nml_host_stop_training_thread(host, /* join */ true);
}
}
void ml_cancel_training_thread(RRDHOST *rh) {
if (rh && rh->ml_host) {
nml_host_t *host = reinterpret_cast<nml_host_t *>(rh->ml_host);
nml_host_stop_training_thread(host, /* join */ false);
}
}
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